Measurement Research Based on Bayesian Structural Equation Cognitive Model

The Bayesian structural equation model integrates the principles of Bayesian statistics, providing a more flexible and comprehensive modeling framework. In exploring complex relationships between variables, handling uncertainty, and dealing with missing data, the Bayesian structural equation model demonstrates unique advantages. Therefore, Bayesian methods are used in this paper to establish a structural equation model of innovative talent cognition, with the measurement of college students’ cognition of innovative talent being studied. An in-depth analysis is conducted on the effects of innovative self-efficacy, social resources, innovative personality traits, and school education, aiming to explore the factors influencing college students’ innovative talent. The results indicate that innovative self-efficacy plays a key role in perception, social resources are significantly positively correlated with the perception of innovative talents, innovative personality tendencies and school education are positively correlated with the perception of innovative talents, but the impact is not significant.

Visual Representation and Cognitive Models in Information Visualization

As a branch of computer science,information visualization aims to help users understand and analyze complex data through graphical interfaces and interactive technologies.Information visualization primarily includes various visual structures such as time-series structures,spatial relationship structures,statistical distribution structures,and geographic map structures,each with unique functions and application scenarios.To better explain the cognitive process of visualization,researchers have proposed various cognitive models based on interaction mechanisms,visual perception steps,and novice use of visualization.These models help understand user cognition in information visualization,enhancing the effectiveness of data analysis and decision-making.

Rotating magnetic field inhibits Aβ protein aggregation and alleviates cognitive impairment in Alzheimer’s disease mice

Amyloid beta(Aβ)monomers aggregate to form fibrils and amyloid plaques,which are critical mechanisms in the pathogenesis of Alzheimer’s disease(AD).Given the important role of Aβ1-42 aggregation in plaque formation,leading to brain lesions and cognitive impairment,numerous studies have aimed to reduce Aβaggregation and slow AD progression.The diphenylalanine(FF)sequence is critical for amyloid aggregation,and magnetic fields can affect peptide alignment due to the diamagnetic anisotropy of aromatic rings.In this study,we examined the effects of a moderate-intensity rotating magnetic field(RMF)on Aβaggregation and AD pathogenesis.Results indicated that the RMF directly inhibited Aβamyloid fibril formation and reduced Aβ-induced cytotoxicity in neural cells in vitro.Using the AD mouse model APP/PS1,RMF restored motor abilities to healthy control levels and significantly alleviated cognitive impairments,including exploration and spatial and non-spatial memory abilities.Tissue examinations demonstrated that RMF reduced amyloid plaque accumulation,attenuated microglial activation,and reduced oxidative stress in the APP/PS1 mouse brain.These findings suggest that RMF holds considerable potential as a non-invasive,high-penetration physical approach for AD treatment.

Evaluation and analysis of neurocognitive dysfunction in patients with colorectal cancer after radical resection: A retrospective study

BACKGROUND With the continuous progress of colorectal cancer treatment technology,the survival rate of patients has improved significantly,but the problem of postoperative neurocognitive dysfunction has gradually attracted attention.AIM To analyze the risk factors for delayed postoperative neurocognitive recovery(DNR)after laparoscopic colorectal cancer surgery and constructed a risk prediction model to provide an evidence-based reference for the prevention and treatment of DNR after laparoscopic colorectal cancer surgery.METHODS The clinical data of 227 patients with colorectal cancer who underwent laparoscopic surgery and regional cerebral saturation oxygenation(rScO2)monitoring at our hospital from March 2020 to July 2022 were retrospectively analyzed.Common factors and potential factors affecting postoperative DNR were used as analysis variables,and univariate analysis and multifactor analysis were carried out step by step to determine the predictors of the model and construct a risk prediction model.The predictive performance of the model was assessed by the receiver operating characteristic(ROC)curve,the calibration curve was used to assess the fit of the model to the data,and a nomogram was drawn.In addition,30 patients who met the inclusion and exclusion criteria from January 2023 to July 2023 were selected for external verification of the prediction model.RESULTS The incidence of postoperative DNR in the modeling group was 15.4%(35/227).Multivariate analysis revealed that age,years of education,diabetes status,and the lowest rScO2 value were the independent influencing factors of postoperative DNR(all P<0.05).Accordingly,a DNR risk prediction model was constructed after laparoscopic colorectal cancer surgery.The area under the ROC curve of the model was 0.757(95%CI:0.676-0.839,P<0.001),and the Hosmer-Lemeshow test of the calibration curve suggested that the model was well fitted(P=0.516).The C-index for external validation of the row was 0.617.CONCLUSION The DNR risk prediction model associated with rScO2 monitoring can be used for individualized assessment of patients undergoing laparoscopic colorectal cancer surgery and provides a clinical basis for the prevention of DNR after surgery.

Modeling of cognitive framework in time-stressed decision making

An approach for modeling a human cognitive framework in time-stressed decision making is presented. The recognitive and metacognitive processes that represent the cognitive framework are modeled by the colored Petri nets （CPNs）. A structural and behavioral analysis method is adopted to obtain the static and dynamic property used to verify the CPNs model of the cognitive framework. Finally, an example from the command and control radar recognition system is used to evaluate the feasibility and availability of the CPNs model adopted in practical systems.

MODELING RADIO RESOURCE MANAGEMENT IN COGNITIVE RADIO SYSTEM BASED ON OFDMA USING COLORED PETRI NET

Cognitive Radio(CR) system based on Orthogonal Frequency Division Multiple Access(OFDMA),such as Wireless Regional Area Networks(WRAN) and Worldwide Interoperability for Microwave Access(WiMAX),often attempt to improve performance via dynamic radio resource management,which is characterized as concurrent processing of different traffic and nondeterministic system capacity.It is essential to design and evaluate such complex system using proper modeling and analysis tools.In the previous work,most of the communication systems were modeled as Markov Chain(MC) and Stochastic Petri Nets(SPN),which have the explicit limitation in evaluating adaptive OFDMA CR system with wide area traffic.In this paper,we develop an executable top-down hier-archical Colored Petri Net(CPN) model for adaptive OFDMA CR system,and analyze its performance using CPN tools.The results demonstrate that the CPN can model different radio resource manage-ment algorithms in CR Systems,and the CPN tools require less computational effort than Markov model using Matlab,with its flexibility and adaptability to the traffics which arrival interval and processing time are not exponentially distributed.

Holistic Discourse in the Network Cognitive Modeling

The purpose of this paper is to pose a new question to speed-up mutual understanding among team members or/and group of experts when communicating over the Internet in forms of virtual collaboration, electronic brainstorming, network strategic conversation, etc. We have previously proposed an approach that the convergent control mechanism based on the fundamental principles of thermodynamic and inverse problem solution method, as well as various artificial intelligence techniques, be incorporated into the communicative process. This paper shows a further development of the approach in terms of applying The Fuzzy Tychonoff Theorem along with quantum techniques provide to reach a high level of holistic discourse which is achieved not only through the application of fundamental principles of compactness of the topological space, but also utilizing quantum entanglement and complementarity principles for discourse structuring in a special way. The approach is implemented as the Responsibility Thinking System （RTS） tested in the course of finding the decisions of the real life issues.

A New Control Strategy for Modeling Wind Energy Systems Using Fuzzy Cognitive Maps

Wind energy is currently a fast-growing interdisciplinary field that encompasses many different branches of engineering and science. Modeling and controlling wind energy systems are difficult and challenging problems. The basic structure of wind turbines and some wind control system methods are briefly reviewed. The need for using advanced theories from fuzzy and intelligent systems in studying wind energy systems is identified and justified. FCMs （fuzzy cognitive maps） are used to model wind energy systems. Simulation studies are performed and obtained results are discussed. A new mathematical approach has been proposed to model dynamical complex systems, the DYFUKN （dynamic fuzzy knowledge networks）. Many open problems in the areas of modeling and controlling wind energy systems are outlined.

Design of Simulation Competition Platform Based on Cognitive Behavior Modeling

Cognitive behavior modeling of agent is an important component of simulation system,and there are some difficulties in the simulation of course teaching.When students make simulation experiments about cognitive behavior modeling,such as algorithm design and model construction,there is no simulation competition platform that is controllable,flexible and scalable.To solve this problem,we propose a simulation competition platform based on cognitive behavior modeling,called TankSim,for undergraduate and graduate students.This platform aims to cultivate studenfs team collaboration and innovation capability,and improve their learning motivation.This paper elaborates the proposed platform from three aspects,including demand analysis,platform design,and content design.

THEORY AND IMPLEMENTATION OF ICAI COGNITIVE MODEL BASED ON MEANING

Cognitive models must be able to adapt the students learning behaviors dynamically.In our point of view,the processes of learning and understanding are,in nature,the procedure that gains the meaning of the object to be learned.So,ICAI cognitive models should reflect the meaning structure of the domain knowledge in students mind.According to this view,we developed the meaning theory of Ludwig Wittgenstein,and proposed the concept of meaning conjoinism.On the basis of the meaning conjoinism we proposed a meaning oriented ICAI cognitive model and its corresponding teaching tactics.Furthermore,we developed an ICAI system named Thinking and the efficiency of our proposal has been demonstrated.

APPLICATION OF HUMAN COGNITIVE MODEL FOR TIME DEPENDENT OPERATOR BEHAVIOR IN CHINESE NPP

This paper discusses some issues on human reliability model of time dependent human behavior. Some results of the crew reliability experiment on Tsinghua training simulator in China are given, Meanwhile, a case of calculation for human error probability during anticipated transient without scram (ATWS) based on the data drew from the recent experiment is offered.

Research on cognitive model of English major writing course based on the Internet

With the development of Internet technology, network is more and more common in the teaching process. On the analysis of teaching status of English major writing course and in the guide of cognitive linguistics and constructivism, the paper studies the use of the internet in English major writing teaching cognitive model.

Mesenchymal stem cell-derived exosomes promote neurogenesis and cognitive function recovery in a mouse model of Alzheimer’s disease

Studies have shown that mesenchymal stem cell-derived exosomes can enhance neural plasticity and improve cognitive impairment.The purpose of this study was to investigate the effects of mesenchymal stem cell-derived exosomes on neurogenesis and cognitive capacity in a mouse model of Alzheimer’s disease.Alzheimer’s disease mouse models were established by injection of beta amyloid 1?42 aggregates into dentate gyrus bilaterally.Morris water maze and novel object recognition tests were performed to evaluate mouse cognitive deficits at 14 and 28 days after administration.Afterwards,neurogenesis in the subventricular zone was determined by immunofluorescence using doublecortin and PSA-NCAM antibodies.Results showed that mesenchymal stem cells-derived exosomes stimulated neurogenesis in the subventricular zone and alleviated beta amyloid 1?42-induced cognitive impairment,and these effects are similar to those shown in the mesenchymal stem cells.These findings provide evidence to validate the possibility of developing cell-free therapeutic strategies for Alzheimer’s disease.All procedures and experiments were approved by Institutional Animal Care and Use Committee(CICUAL)(approval No.CICUAL 2016-011)on April 25,2016.

Amelioration of Alzheimer's disease pathology and cognitive deficits by immunomodulatory agents in animal models of Alzheimer's disease

The most common age-related neurodegenerative disease is Alzheimer's disease(AD) characterized by aggregated amyloid-β(Aβ) peptides in extracellular plaques and aggregated hyperphosphorylated tau protein in intraneuronal neurofibrillary tangles,together with loss of cholinergic neurons,synaptic alterations,and chronic inflammation within the brain.These lead to progressive impairment of cognitive function.There is evidence of innate immune activation in AD with microgliosis.Classically-activated microglia(M1 state) secrete inflammatory and neurotoxic mediators,and peripheral immune cells are recruited to inflammation sites in the brain.The few drugs approved by the US FDA for the treatment of AD improve symptoms but do not change the course of disease progression and may cause some undesirable effects.Translation of active and passive immunotherapy targeting Aβ in AD animal model trials had limited success in clinical trials.Treatment with immunomodulatory/anti-inflammatory agents early in the disease process,while not preventive,is able to inhibit the inflammatory consequences of both Aβ and tau aggregation.The studies described in this review have identified several agents with immunomodulatory properties that alleviated AD pathology and cognitive impairment in animal models of AD.The majority of the animal studies reviewed had used transgenic models of early-onset AD.More effort needs to be given to creat models of late-onset AD.The effects of a combinational therapy involving two or more of the tested pharmaceutical agents,or one of these agents given in conjunction with one of the cell-based therapies,in an aged animal model of AD would warrant investigation.

Cold water swimming pretreatment reduces cognitive deficits in a rat model of traumatic brain injury

A moderate stress such as cold water swimming can raise the tolerance of the body to potentially injurious events. However, little is known about the mechanism of beneficial effects induced by moderate stress. In this study, we used a classic rat model of traumatic brain injury to test the hypothesis that cold water swimming preconditioning improved the recovery of cognitive functions and explored the mechanisms. Results showed that after traumatic brain injury, pre-conditioned rats（cold water swimming for 3 minutes at 4℃） spent a significantly higher percent of times in the goal quadrant of cold water swim, and escape latencies were shorter than for non-pretreated rats. The number of circulating endothelial progenitor cells was significantly higher in pre-conditioned rats than those without pretreatment at 0, 3, 6 and 24 hours after traumatic brain injury. Immunohistochemical staining and Von Willebrand factor staining demonstrated that the number of CD34~＋ stem cells and new blood vessels in the injured hippocampus tissue increased significantly in pre-conditioned rats. These data suggest that pretreatment with cold water swimming could promote the proliferation of endothelial progenitor cells and angiogenesis in the peripheral blood and hippocampus. It also ameliorated cognitive deficits caused by experimental traumatic brain injury.

Diabetes and cognitive decline:Challenges and future direction

There is growing evidence that diabetes can induce cognitive decline and dementia.It is a slow,progressive cognitive decline that can occur in any age group,but is seen more frequently in older individuals.Symptoms related to cognitive decline are worsened by chronic metabolic syndrome.Animal models are frequently utilized to elucidate the mechanisms of cognitive decline in diabetes and to assess potential drugs for therapy and prevention.This review addresses the common factors and pathophysiology involved in diabetes-related cognitive decline and outlines the various animal models used to study this condition.

Cat Swarm with Fuzzy Cognitive Maps for Automated Soil Classification

Accurate soil prediction is a vital parameter involved to decide appro-priate crop,which is commonly carried out by the farmers.Designing an auto-mated soil prediction tool helps to considerably improve the efficacy of the farmers.At the same time,fuzzy logic(FL)approaches can be used for the design of predictive models,particularly,Fuzzy Cognitive Maps(FCMs)have involved the concept of uncertainty representation and cognitive mapping.In other words,the FCM is an integration of the recurrent neural network(RNN)and FL involved in the knowledge engineering phase.In this aspect,this paper introduces effective fuzzy cognitive maps with cat swarm optimization for automated soil classifica-tion(FCMCSO-ASC)technique.The goal of the FCMCSO-ASC technique is to identify and categorize seven different types of soil.To accomplish this,the FCMCSO-ASC technique incorporates local diagonal extrema pattern(LDEP)as a feature extractor for producing a collection of feature vectors.In addition,the FCMCSO model is applied for soil classification and the weight values of the FCM model are optimally adjusted by the use of CSO algorithm.For exam-ining the enhanced soil classification outcomes of the FCMCSO-ASC technique,a series of simulations were carried out on benchmark dataset and the experimen-tal outcomes reported the enhanced performance of the FCMCSO-ASC technique over the recent techniques with maximum accuracy of 96.84%.

An enriched environment reduces hippocampal inflammatory response and improves cognitive function in a mouse model of stroke

An enriched environment is used as a behavio ral intervention therapy that applies sensory,motor,and social stimulation,and has been used in basic and clinical research of va rious neurological diseases.In this study,we established mouse models of photothrombotic stroke and,24 hours later,raised them in a standard,enriched,or isolated environment for 4 weeks.Compared with the mice raised in a standard environment,the cognitive function of mice raised in an enriched environment was better and the pathological damage in the hippocampal CA1 region was remarkably alleviated.Furthermore,protein expression levels of tumor necrosis factor receptor-associated factor 6,nuclear factorκB p65,interleukin-6,and tumor necrosis factorα,and the mRNA expression level of tumor necrosis factor receptor-associated factor 6 were greatly lower,while the expression level of miR-146a-5p was higher.Compared with the mice raised in a standard environment,changes in these indices in mice raised in an isolated environment were opposite to mice raised in an enriched environment.These findings suggest that different living environments affect the hippocampal inflammatory response and cognitive function in a mouse model of stro ke.An enriched environment can improve cognitive function following stroke through up-regulation of miR-146a-5p expression and a reduction in the inflammatory response.

Cognitive deficits in schizophrenia:from pharmacology to neurocognitive models

Schizophrenia is a typical mental disorder characterized by cognitive,social,and emotional impairments and by psychotic symptoms.For nearly a century,there have been ongoing discussions on the anatomical-functional connections between brain abnormalities and symptoms in patients with schizophrenia.Neuroimaging studies in such patients show abnormalities in the prefrontal cortex(PFC),a brain region that acts as an executive center in cognition processing.The disrupted brain connectivity between PFC and other brain structures(such as the limbic system,basal ganglia and thalamus)results in faulty information processing and cognition deficits.Dopamine receptors,which have historically acted as vital targets in schizophrenia therapies,have complex roles in cognition.Here we reviewed dopamine's role as a widespread neurotransmitter mediating the PFC-cognitive system.The imbalance of brain dopamine level,especially the abnormal D1/D2receptors ratio,leads to dysfunctions in brain connectivity in patients with schizophrenia.Recent neurocognitive modeling studies suggest the imbalance of dopamine receptors affects the internal noise within brain networks,which may lead to reduced signal-to-noise ratio in the PFC neuron populations.Going forward,more researches focusing on the relationship between pharmacology and neurocognitive models are needed,in an effort to identify more effective and efficient ways to treat cognitive impairment in patients with schizophrenia.

中国对东盟货物贸易出口波动的影响因素研究——基于改进的CMS模型实证分析

推动外贸稳规模、优结构,对推动高质量发展具有重要支撑作用。为了能够更好地研究贸易结构变化对中国出口的影响,文章对CMS模型进口需求结构效应和出口结构效应及两者细分效应的算法进行了调整,并运用改进的CMS模型对中国出口波动的影响因素进行实证分析。同时为了研究各影响因素在重要时期对中国出口的影响,文章将研究周期设定为2008—2022年,包括了全球金融危机和新冠疫情等重大事件。研究发现:(1)中国对东盟商品出口规模大幅增长,主要得益于进口需求规模扩大、出口整体竞争力提升,以及两者交互作用的整体交互效应。在结构上表现为进口需求结构效应显著促进出口,出口结构效应抑制出口的特征。(2)出口结构效应抑制出口主要是因为我国出口集中在出口效应较低的国家和商品上。(3)在东盟面临危机时,需求驱动的增长模式和本来就抑制出口的出口结构,对中国出口的负面影响更加明显。因此,为了促进中国对东盟出口平稳增长,需要推动传统产业转型升级和大力发展战略性新兴产业,来提高中国商品出口竞争力;充分利用好RCEP减税和原产地累积等规则挖掘商机;积极推进中国—东盟自由贸易区3.0版谈判,全面提升中国—东盟经贸制度型开放水平,在数字经济和绿色能源经济等领域加强与东盟的合作,培育双边贸易新的增长点。